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Author: Simant Dube Publisher: Springer Nature ISBN: 3030686248 Category : Computers Languages : en Pages : 355
Book Description
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
Author: Simant Dube Publisher: Springer Nature ISBN: 3030686248 Category : Computers Languages : en Pages : 355
Book Description
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
Author: Anirudh Koul Publisher: "O'Reilly Media, Inc." ISBN: 1492034819 Category : Computers Languages : en Pages : 585
Book Description
Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
Author: Christoph Molnar Publisher: Lulu.com ISBN: 0244768528 Category : Computers Languages : en Pages : 320
Book Description
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Author: Norman Matloff Publisher: No Starch Press ISBN: 1718502109 Category : Computers Languages : en Pages : 271
Book Description
Learn to expertly apply a range of machine learning methods to real data with this practical guide. Packed with real datasets and practical examples, The Art of Machine Learning will help you develop an intuitive understanding of how and why ML methods work, without the need for advanced math. As you work through the book, you’ll learn how to implement a range of powerful ML techniques, starting with the k-Nearest Neighbors (k-NN) method and random forests, and moving on to gradient boosting, support vector machines (SVMs), neural networks, and more. With the aid of real datasets, you’ll delve into regression models through the use of a bike-sharing dataset, explore decision trees by leveraging New York City taxi data, and dissect parametric methods with baseball player stats. You’ll also find expert tips for avoiding common problems, like handling “dirty” or unbalanced data, and how to troubleshoot pitfalls. You’ll also explore: How to deal with large datasets and techniques for dimension reduction Details on how the Bias-Variance Trade-off plays out in specific ML methods Models based on linear relationships, including ridge and LASSO regression Real-world image and text classification and how to handle time series data Machine learning is an art that requires careful tuning and tweaking. With The Art of Machine Learning as your guide, you’ll master the underlying principles of ML that will empower you to effectively use these models, rather than simply provide a few stock actions with limited practical use. Requirements: A basic understanding of graphs and charts and familiarity with the R programming language
Author: National Academies of Sciences, Engineering, and Medicine Publisher: National Academies Press ISBN: 0309684234 Category : Computers Languages : en Pages : 148
Book Description
Information technology (IT) is widely understood to be the enabling technology of the 21st century. IT has transformed, and continues to transform, all aspects of our lives: commerce and finance, education, energy, health care, manufacturing, government, national security, transportation, communications, entertainment, science, and engineering. IT and its impact on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow in size and importance. IT’s impacts on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow. IT enabled innovation and advances in IT products and services draw on a deep tradition of research and rely on sustained investment and a uniquely strong partnership in the United States among government, industry, and universities. Past returns on federal investments in IT research have been extraordinary for both U.S. society and the U.S. economy. This IT innovation ecosystem fuels a virtuous cycle of innovation with growing economic impact. Building on previous National Academies work, this report describes key features of the IT research ecosystem that fuel IT innovation and foster widespread and longstanding impact across the U.S. economy. In addition to presenting established computing research areas and industry sectors, it also considers emerging candidates in both categories.
Author: Nick Bostrom Publisher: ISBN: 0199678111 Category : Computers Languages : en Pages : 353
Book Description
This profoundly ambitious and original book picks its way carefully through a vast tract of forbiddingly difficult intellectual terrain.
Author: Richard S. Sutton Publisher: MIT Press ISBN: 0262352702 Category : Computers Languages : en Pages : 549
Book Description
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Author: Prof. Dr. Bilal Semih Bozdemir Publisher: Prof. Dr. Bilal Semih Bozdemir ISBN: Category : Fiction Languages : en Pages : 462
Book Description
Humans and the Third Dimension; A Journey of Discovery The Limits of Our Perceptions Our Three-Dimensional World: A Familiar Reality Space and Time: Basic Concepts The Limits of Human Perception: Sight, Hearing, Touch Other Senses: Smell and Taste The Sixth Sense: Intuition and Insight The Subconscious and the Superconscious: Hidden Worlds Dreams and Reality: Is There a Difference? Parallel Universes: Possibilities and Scenarios Quantum Physics: On the Nature of Reality Quantum Entanglement: Separate But Connected Superposition: Being in More Than One State Quantum Examples: Reflections in Daily Life Time Travel: Is It Possible? The Theory of Relativity of Time: Einstein's Legacy Black Holes: The End of Time? Wormholes: Transitioning from One Dimension to Another The Theory of the Multiverse: Infinite Possibilities The Fourth Dimension and Beyond: Challenges of Conceptualization Human Consciousness and Dimensions: Is There a Connection? Aura and Energy Fields: Invisible Worlds Meditation and Consciousness Expansion: New Perspectives Astral Travel: Unconscious Experiences Telepathy and Remote Influence: Mind Power Dream Interpretation: Signs of the Subconscious Kabbalah and Dimensions: The View of the Ancient Sages Buddhism and Dimensions: Spiritual Development Hinduism and Dimensions: Karma and Reincarnation Shamanism and Dimensions: Spiritual Journeys Human Body and Energy Centers: Chakras Chakra Balancing and Healing: Holistic Approach Frequencies and Vibrations: The Language of Energy Crystals and Energy: Healing and Balance Reiki and Energy Healing: Modern Applications Spiritual Applications: Interdimensional Connections Traces of the Unseen World: Historical Examples Mysterious Events: The Unexplained Phenomenon UFOs and Aliens: Fact or Fiction? Exploration of the Unknown: A Continuous Process Man's Place in the Universe: Existential Questions
Author: Kence Anderson Publisher: "O'Reilly Media, Inc." ISBN: 1098110706 Category : Computers Languages : en Pages : 253
Book Description
Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs
Author: Issa, Tomayess Publisher: IGI Global ISBN: 1466681489 Category : Computers Languages : en Pages : 446
Book Description
Web technologies have become a vital element within educational, professional, and social settings as they have the potential to improve performance and productivity across organizations. Artificial Intelligence Technologies and the Evolution of Web 3.0 brings together emergent research and best practices surrounding the effective usage of Web 3.0 technologies in a variety of environments. Featuring the latest technologies and applications across industries, this publication is a vital reference source for academics, researchers, students, and professionals who are interested in new ways to use intelligent web technologies within various settings.
Author: Simant Dube
Author: Simant Dube
Author: Anirudh Koul
Author: Christoph Molnar
Author: Norman Matloff
Author: National Academies of Sciences, Engineering, and Medicine
Author: Nick Bostrom
Author: Richard S. Sutton
Author: Prof. Dr. Bilal Semih Bozdemir
Author: Kence Anderson
Author: Issa, Tomayess